Mammary Tumor-Associated RNAs Impact Tumor Cell Proliferation, Invasion, and Migration

Organoids derived from metastatic cancers: Present and future

Organoids are three-dimensional structures derived from primary tissue or tumors that closely mimic the architecture, histology, and function of the parental tissue. In recent years, patient-derived organoids (PDOs) have emerged as powerful tools for modeling tumor heterogeneity, drug screening, and personalized medicine. Although most cancer organoids are derived from primary tumors, the ability of organoids from metastatic cancer to serve as a model for studying tumor biology and predicting the therapeutic response is an area of active investigation. Recent studies have shown that organoids derived from metastatic sites can provide valuable insights into tumor biology and may be used to validate predictive models of the drug response. In this comprehensive review, we discuss the feasibility of culturing organoids from multiple metastatic cancers and evaluate their potential for advancing basic cancer research, drug development, and personalized therapy. We also explore the limitations and challenges associated with using metastasis organoids for cancer research. Overall, this review provides a comprehensive overview of the current state and future prospects of metastatic cancer-derived organoids.

Targeting and engineering long non-coding RNAs for cancer therapy

RNA therapeutics (RNATx) aim to treat diseases, including cancer, by targeting or employing RNA molecules for therapeutic purposes. Amongst the most promising targets are long non-coding RNAs (lncRNAs), which regulate oncogenic molecular networks in a cell type-restricted manner. lncRNAs are distinct from protein-coding genes in important ways that increase their therapeutic potential yet also present hurdles to conventional clinical development. Advances in genome editing, oligonucleotide chemistry, multi-omics and RNA engineering are paving the way for efficient and cost-effective lncRNA-focused drug discovery pipelines. In this Review, we present the emerging field of lncRNA therapeutics for oncology, with emphasis on the unique strengths and challenges of lncRNAs within the broader RNATx framework. We outline the necessary steps for lncRNA therapeutics to deliver effective, durable, tolerable and personalized treatments for cancer.

Identification of glioblastoma stem cell-associated lncRNAs using single-cell RNA sequencing datasets

Glioblastoma multiforme (GBM) is an aggressive, heterogeneous brain tumor in which glioblastoma stem cells (GSCs) are known culprits of therapy resistance. Long non-coding RNAs (lncRNAs) have been shown to play a critical role in both cancer and normal biology. A few studies have suggested that aberrant expression of lncRNAs is associated with GSCs. However, a comprehensive single-cell analysis of the GSC-associated lncRNA transcriptome has not been carried out. Here, we analyzed recently published single-cell RNA sequencing datasets of adult GBM tumors, GBM organoids, GSC-enriched GBM tumors, and developing human brain samples to identify lncRNAs highly expressed in GSCs. We further revealed that the GSC-specific lncRNAs GIHCG and LINC01563 promote proliferation, migration, and stemness in the GSC population. Together, this study identified a panel of uncharacterized GSC-enriched lncRNAs and set the stage for future in-depth studies to examine their role in GBM pathology and their potential as biomarkers and/or therapeutic targets in GBM.

PD-L1-related IncRNAs are associated with malignant characteristics and immune microenvironment in glioma

BACKGROUND

The expression of long non-coding RNA (lncRNA) can function as diagnostic and therapeutic biomarker for tumors. This research explores the role of PD-L1-related lncRNAs in affecting malignant characteristics and the immune microenvironment of glioma.

METHODS

Downloading gene expression profiles and clinicopathological information of glioma from TCGA and CGGA databases, 6 PD-L1-related lncRNAs were identified through correlation analysis, Cox and LASSO regression analysis, establishing the risk score model based on them. Bioinformatics analysis and cell experiments in vitro were adopted to verify the effects of LINC01271 on glioma.

RESULTS

Risk scores based on 6 PD-L1-related lncRNAs (AL355974.3, LINC01271, AC011899.3, MIR4500HG, LINC02594, AL357055.3) can reflect malignant characteristics and immunotherapy response of glioma. Patients with high LINC01271 expression had a worse prognosis, a higher abundance of M1 subtype macrophages in the immune microenvironment, and a higher degree of tumor malignancy. Experiments in vitro confirmed its positive regulatory effect on the proliferation and migration of glioma cells.

CONCLUSIONS

The risk score model based on 6 PD-L1-related lncRNAs can reflect the malignant characteristics and prognosis of glioma. LINC01271 can independently be used as a new target for prognosis evaluation and therapy.

In vitro evaluation of the anti‑breast cancer properties and gene expression profiles of Thai traditional formulary medicine extracts

Breast cancer is a leading cause of cancer-related deaths worldwide. Moreover, standard treatments are limited, so new alternative treatments are required. Thai traditional formulary medicine (TTFM) utilizes certain herbs to treat different diseases due to their dominant properties including anti-fungal, anti-bacterial, antigenotoxic, anti-inflammatory and anti-cancer actions. However, very little is known about the anti-cancer properties of TTFM against breast cancer cells and the underlying molecular mechanism has not been elucidated. Therefore, the present study, evaluated the metabolite profiles of TTFM extracts, the anti-cancer activities of TTFM extracts, their effects on the apoptosis pathway and associated gene expression profiles. Liquid chromatography with tandem mass spectroscopy analysis identified a total of 226 compounds within the TTFM extracts. Several of these compounds have been previously shown to have an anti-cancer effect in certain cancer types. The MTT results demonstrated that the TTFM extracts significantly reduced the cell viability of the breast cancer 4T1 and MDA-MB-231 cell lines. Moreover, an apoptosis assay, demonstrated that the TTFM extracts significantly increased the proportion of apoptotic cells. Furthermore, the RNA-sequencing results demonstrated that 25 known genes were affected by TTFM treatment in 4T1 cells. TTFM treatment significantly up-regulated Slc5a8 and Arhgap9 expression compared with untreated cells. Moreover, Cybb, and Bach2os were significantly downregulated after TTFM treatment compared with untreated cells. Reverse transcription-quantitative PCR demonstrated that TTFM extract treatment significantly increased Slc5a8 and Arhgap9 mRNA expression levels and significantly decreased Cybb mRNA expression levels. Moreover, the mRNA expression levels of Bax and Casp9 were significantly increased after TTFM treatment in 4T1 cells compared with EpH4-Ev cells. These findings indicated anti-breast cancer activity via induction of the apoptotic process. However, further experiments are required to elucidate how TTFM specifically regulates genes and proteins. This study supports the potential usage of TTFM extracts for the development of anti-cancer drugs.

PTHrP Regulates Fatty Acid Metabolism via Novel lncRNA in Breast Cancer Initiation and Progression Models

Parathyroid hormone-related peptide (PTHrP) is the primary cause of malignancy-associated hypercalcemia (MAH). We previously showed that PTHrP ablation, in the MMTV-PyMT murine model of breast cancer (BC) progression, can dramatically prolong tumor latency, slow tumor growth, and prevent metastatic spread. However, the signaling mechanisms using lineage tracing have not yet been carefully analyzed. Here, we generated Pthrpflox/flox; Cre+ mT/mG mice (KO) and Pthrpwt/wt; Cre+ mT/mG tumor mice (WT) to examine the signaling pathways under the control of PTHrP from the early to late stages of tumorigenesis. GFP+ mammary epithelial cells were further enriched for subsequent RNA sequencing (RNAseq) analyses. We observed significant upregulation of cell cycle signaling and fatty acid metabolism in PTHrP WT tumors, which are linked to tumor initiation and progression. Next, we observed that the expression levels of a novel lncRNA, GM50337, along with stearoyl-Coenzyme A desaturase 1 (Scd1) are significantly upregulated in PTHrP WT but not in KO tumors. We further validated a potential human orthologue lncRNA, OLMALINC, together with SCD1 that can be regulated via PTHrP in human BC cell lines. In conclusion, these novel findings could be used to develop targeted strategies for the treatment of BC and its metastatic complications.

Redefining normal breast cell populations using long noncoding RNAs

Single-cell RNAseq has allowed unprecedented insight into gene expression across different cell populations in normal tissue and disease states. However, almost all studies rely on annotated gene sets to capture gene expression levels and sequencing reads that do not align to known genes are discarded. Here, we discover thousands of long noncoding RNAs (lncRNAs) expressed in human mammary epithelial cells and analyze their expression in individual cells of the normal breast. We show that lncRNA expression alone can discriminate between luminal and basal cell types and define subpopulations of both compartments. Clustering cells based on lncRNA expression identified additional basal subpopulations, compared to clustering based on annotated gene expression, suggesting that lncRNAs can provide an additional layer of information to better distinguish breast cell subpopulations. In contrast, these breast-specific lncRNAs poorly distinguish brain cell populations, highlighting the need to annotate tissue-specific lncRNAs prior to expression analyses. We also identified a panel of 100 breast lncRNAs that could discern breast cancer subtypes better than protein-coding markers. Overall, our results suggest that lncRNAs are an unexplored resource for new biomarker and therapeutic target discovery in the normal breast and breast cancer subtypes.

Identification of glioblastoma stem cell-associated lncRNAs using single-cell RNA-sequencing datasets

Glioblastoma multiforme (GBM) is an aggressive, heterogeneous grade IV brain tumor. Glioblastoma stem cells (GSCs) initiate the tumor and are known culprits of therapy resistance. Mounting evidence has demonstrated a regulatory role of long non-coding RNAs (lncRNAs) in various biological processes, including pluripotency, differentiation, and tumorigenesis. A few studies have suggested that aberrant expression of lncRNAs is associated with GSCs. However, a comprehensive single-cell analysis of the GSC-associated lncRNA transcriptome has not been carried out. Here, we analyzed recently published single-cell RNA-sequencing datasets of adult human GBM tumors, GBM organoids, GSC-enriched GBM tumors, and developing human brains to identify lncRNAs highly expressed in GBM. To categorize GSC populations in the GBM tumors, we used the GSC marker genes SOX2, PROM1, FUT4, and L1CAM. We found three major GSC population clusters: radial glia, oligodendrocyte progenitor cells, and neurons. We found 10â€"100 lncRNAs significantly enriched in different GSC populations. We also validated the level of expression and localization of several GSC-enriched lncRNAs using qRT-PCR, single-molecule RNA FISH, and sub-cellular fractionation. We found that the radial glia GSC-enriched lncRNA PANTR1 is highly expressed in GSC lines and is localized to both the cytoplasmic and nuclear fractions. In contrast, the neuronal GSC-enriched lncRNAs LINC01563 and MALAT1 are highly enriched in the nuclear fraction of GSCs. Together, this study identified a panel of uncharacterized GSC-specific lncRNAs. These findings set the stage for future in-depth studies to examine their role in GBM pathology and their potential as biomarkers and/or therapeutic targets in GBM.

Inflammatory signaling on cytochrome P450-mediated drug metabolism in hepatocytes

Cytochrome P450 (CYP450) enzymes are membrane-bound blood proteins that are vital to drug detoxification, cell metabolism, and homeostasis. CYP450s belonging to CYP families 1-3 are responsible for nearly 80% of oxidative metabolism and complete elimination of approximately 50% of all common clinical drugs in humans liver hepatocytes. CYP450s can affect the body's response to drugs by altering the reaction, safety, bioavailability, and toxicity. They can also regulate metabolic organs and the body's local action sites to produce drug resistance through altered drug metabolism. Genetic polymorphisms in the CYP gene alone do not explain ethnic and individual differences in drug efficacy in the context of complex diseases. The purpose of this review is to summarize the impact of new inflammatory-response signaling pathways on the activity and expression of CYP drug-metabolizing enzymes. Included is a summary of recent studies that have identified drugs with the potential to regulate drug-metabolizing enzyme activity. Our goal is to inspire the development of clinical drug treatment processes that consider the impact of the inflammatory environment on drug treatment, as well as provide research targets for those studying drug metabolism.

Cerebral Organoids and Antisense Oligonucleotide Therapeutics: Challenges and Opportunities

The advent of stem cell-derived cerebral organoids has already advanced our understanding of disease mechanisms in neurological diseases. Despite this, many remain without effective treatments, resulting in significant personal and societal health burden. Antisense oligonucleotides (ASOs) are one of the most widely used approaches for targeting RNA and modifying gene expression, with significant advancements in clinical trials for epilepsy, neuromuscular disorders and other neurological conditions. ASOs have further potential to address the unmet need in other neurological diseases for novel therapies which directly target the causative genes, allowing precision treatment. Induced pluripotent stem cell (iPSC) derived cerebral organoids represent an ideal platform in which to evaluate novel ASO therapies. In patient-derived organoids, disease-causing mutations can be studied in the native genetic milieu, opening the door to test personalized ASO therapies and n-of-1 approaches. In addition, CRISPR-Cas9 can be used to generate isogenic iPSCs to assess the effects of ASOs, by either creating disease-specific mutations or correcting available disease iPSC lines. Currently, ASO therapies face a number of challenges to wider translation, including insufficient uptake by distinct and preferential cell types in central nervous system and inability to cross the blood brain barrier necessitating intrathecal administration. Cerebral organoids provide a practical model to address and improve these limitations. In this review we will address the current use of organoids to test ASO therapies, opportunities for future applications and challenges including those inherent to cerebral organoids, issues with organoid transfection and choice of appropriate read-outs.

Long non-coding RNA lncHUPC1 induced by FOXA1 promotes tumor progression by inhibiting apoptosis via miR-133b/SDCCAG3 in prostate cancer

Long non-coding RNAs (lncRNAs) were confirmed to be involved in regulating various malignant behaviors of tumor cells in prostate cancer (PCa). Using The Cancer Genome Atlas (TCGA) prostate adenocarcinoma datasets, several endogenous competing RNA (ceRNA) networks of lncRNA/miRNA/mRNA associated with the progression-free survival (PFS) and Gleason score (GS) were identified using bioinformatics analysis. lncRNA AC004447.2 (lncHUPC1, ENSG00000269131)/miR-133b/serologically defined colon cancer antigen-3 (SDCCAG3) was a newly identified ceRNA network that affected cell growth and apoptosis in PCa. Using q-PCR, lncHUPC1 and SDCCAG3 were found to be up-regulated in PCa cells, while miR-133b was down-regulated. The same results were found in tissue samples from 70 PCa cases. It was confirmed that the knockdown of lncHUPC1 increased the expression of miR-133b and decreased that of SDCCAG3, which further increased apoptosis and inhibited cell growth, while the miR-133b inhibitor partially reversed these effects. After transfection with miR-133b mimic after lncHUPC1-knockdown, the expression of miR-133b increased while that of SDCCAG3 reduced, and the apoptosis of the cells was more obvious and the growth of the cells was slower. Therefore, lncHUPC1 was confirmed to regulate SDCCAG3 by binding to miR-133b. Additionally, we found that the transcription factor Forkhead Box A1 (FOXA1) directly bound to the promoter of lncHUPC1 to activate it. In conclusion, the ceRNA network of lncHUPC1/miR-133b/SDCCAG3 affected the growth and apoptosis of PCa cells, and FOXA1 may be involved in the process as a transcription factor of lncHUPC1.

Long-chain non-coding RNA UCA1 inhibits renal tubular epithelial cell apoptosis by targeting microRNA-206 in diabetic nephropathy

In this study, the inhibitory effect of long-chain non-coding RNA urothelial carcinoma associated 1 (UCA1) on renal tubular epithelial cell apoptosis by targeting microRNA (miRNA)-206 in diabetic nephropathy (DN) was investigated through DN rat model. The results showed that UCA1 expression was significantly reduced in diabetic renal tubular epithelial tissues and HG-induced HK-2 cells. UCA1 significantly inhibited HG-induced apoptosis and inflammation of renal tubular epithelial cells in HK-2 cells. In addition, UCA1 can directly act as an anti-pro-cytokine by inhibiting the expression of miR-206, and finally inhibit the apoptosis and inflammation of renal tubular epithelial cells. We conclude that UCA1 inhibits renal tubular epithelial cell apoptosis by targeting miRNA-206 in DN and can be used as a potential therapeutic target for DN.

Noncoding RNAs: biology and applications-a Keystone Symposia report

The human transcriptome contains many types of noncoding RNAs, which rival the number of protein-coding species. From long noncoding RNAs (lncRNAs) that are over 200 nucleotides long to piwi-interacting RNAs (piRNAs) of only 20 nucleotides, noncoding RNAs play important roles in regulating transcription, epigenetic modifications, translation, and cell signaling. Roles for noncoding RNAs in disease mechanisms are also being uncovered, and several species have been identified as potential drug targets. On May 11-14, 2021, the Keystone eSymposium "Noncoding RNAs: Biology and Applications" brought together researchers working in RNA biology, structure, and technologies to accelerate both the understanding of RNA basic biology and the translation of those findings into clinical applications.

The potential application of organoids in breast cancer research and treatment

Tumor heterogeneity is a major challenge for breast cancer researchers who have struggled to find effective treatments despite recent advances in oncology. Although the use of 2D cell culture methods in breast cancer research has been effective, it cannot model the heterogeneity of breast cancer as found within the body. The development of 3D culture of tumor cells and breast cancer organoids has provided a new approach in breast cancer research, allowing the identification of biomarkers, study of the interaction of tumor cells with the microenvironment, and for drug screening and discovery. In addition, the possibility of gene editing in organoids, especially using the CRISPR/Cas9 system, is convenient, and has allowed a more detailed study of tumor behavior in models closer to the physiological condition. The present review covers the application of organoids in breast cancer research. The recent use of gene-editing systems to provide insights into therapeutic approaches for breast cancer, is highlighted. The study of organoids and the possibility of gene manipulation may be a step towards the personalized treatment of breast cancer, which has so far remained unattainable due to the high heterogeneity of breast cancer.

Single-Cell RNA-Seq Reveals Heterogeneous lncRNA Expression in Xenografted Triple-Negative Breast Cancer Cells

Breast cancer is the most commonly diagnosed cancer in the world, with triple-negative breast cancer (TNBC) making up 12% of these diagnoses. TNBC tumours are highly heterogeneous in both inter-tumour and intra-tumour gene expression profiles, where they form subclonal populations of varying levels of aggressiveness. These aspects make it difficult to study and treat TNBC, requiring further research into tumour heterogeneity as well as potential therapeutic targets and biomarkers. Recently, it was discovered that the majority of the transcribed genome comprises non-coding RNAs, in particular long non-coding RNAs (lncRNAs). LncRNAs are transcripts of >200 nucleotides in length that do not encode a protein. They have been characterised as regulatory molecules and their expression can be associated with a malignant phenotype. We set out to explore TNBC tumour heterogeneity in vivo at a single cell level to investigate whether lncRNA expression varies across different cells within the tumour, even if cells are coming from the same cell line, and whether lncRNA expression is sufficient to define cellular subpopulations. We applied single-cell expression profiling due to its ability to capture expression signals of lncRNAs expressed in small subpopulations of cells. Overall, we observed most lncRNAs to be expressed at low, but detectable levels in TNBC xenografts, with a median of 25 lncRNAs detected per cell. LncRNA expression alone was insufficient to define a subpopulation of cells, and lncRNAs showed highly heterogeneous expression patterns, including ubiquitous expression, subpopulation-specific expression, and a hybrid pattern of lncRNAs expressed in several, but not all subpopulations. These findings reinforce that transcriptionally defined tumour cell subpopulations can be identified in cell-line derived xenografts, and uses single-cell RNA-seq (scRNA-seq) to detect and characterise lncRNA expression across these subpopulations in xenografted tumours. Future studies will aim to investigate the spatial distribution of lncRNAs within xenografts and patient tissues, and study the potential of subclone-specific lncRNAs as new therapeutic targets and/or biomarkers.

Transcriptome Analysis Identifies GATA3-AS1 as a Long Noncoding RNA Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients

Breast cancer is one of the leading causes of mortality in women worldwide, and neoadjuvant chemotherapy has emerged as an option for the management of locally advanced breast cancer. Extensive efforts have been made to identify new molecular markers to predict the response to neoadjuvant chemotherapy. Transcripts that do not encode proteins, termed long noncoding RNAs (lncRNAs), have been shown to display abnormal expression profiles in different types of cancer, but their role as biomarkers in response to neoadjuvant chemotherapy has not been extensively studied. Herein, lncRNA expression was profiled using RNA sequencing in biopsies from patients who subsequently showed either response or no response to treatment. The GATA3-AS1 transcript was overexpressed in the nonresponder group and was the most stable feature when performing selection in multiple random forest models. GATA3-AS1 was experimentally validated by RT-qPCR in an extended group of 68 patients. Expression analysis confirmed that GATA3-AS1 is overexpressed primarily in patients who were nonresponsive to neoadjuvant chemotherapy, with a sensitivity of 92.9%, a specificity of 75.0%, and an area under the curve of approximately 0.90, as measured by receiver operating characteristic curve analysis. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74-208.42; P = 0.001); GATA3-AS1 was established as an independent predictor of response. Thus, lncRNA GATA3-AS1 is proposed as a potential predictive biomarker of nonresponse to neoadjuvant chemotherapy.

Epigenetics of Most Aggressive Solid Tumors: Pathways, Targets and Treatments

Highly aggressive tumors are characterized by a highly invasive phenotype, and they display chemoresistance. Furthermore, some of the tumors lack expression of biomarkers for target therapies. This is the case of small-cell lung cancer, triple-negative breast cancer, pancreatic ductal adenocarcinoma, glioblastoma, metastatic melanoma, and advanced ovarian cancer. Unfortunately, these patients show a low survival rate and most of the available drugs are ineffective. In this context, epigenetic modifications have emerged to provide the causes and potential treatments for such types of tumors. Methylation and hydroxymethylation of DNA, and histone modifications, are the most common targets of epigenetic therapy, to influence gene expression without altering the DNA sequence. These modifications could impact both oncogenes and tumor suppressor factors, which influence several molecular pathways such as epithelial-to-mesenchymal transition, WNT/β-catenin, PI3K-mTOR, MAPK, or mismatch repair machinery. However, epigenetic changes are inducible and reversible events that could be influenced by some environmental conditions, such as UV exposure, smoking habit, or diet. Changes in DNA methylation status and/or histone modification, such as acetylation, methylation or phosphorylation, among others, are the most important targets for epigenetic cancer therapy. Therefore, the present review aims to compile the basic information of epigenetic modifications, pathways and factors, and provide a rationale for the research and treatment of highly aggressive tumors with epigenetic drugs.

MaTAR25: a long non-coding RNA involved in breast cancer progression

We recently reported on the role of Mammary Tumor Associated RNA 25 (MaTAR25) in mammary tumor cell proliferation, migration, and invasion. MaTAR25 interacts with transcriptional activator protein Pur-beta (Purb) to regulate its downstream targets such as Tensin1 in trans. The human ortholog of MaTAR25, LINC01271, is upregulated with human breast cancer stage and metastasis.

Applications of Omics Technologies for Three-Dimensional In Vitro Disease Models

Omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, multiomics, and integrated modalities, have greatly contributed to our understanding of various diseases by enabling researchers to probe the molecular wiring of cellular systems in a high-throughput and precise manner. With the development of tissue-engineered three-dimensional (3D) in vitro disease models, such as organoids and spheroids, there is potential of integrating omics technologies with 3D disease models to elucidate the complex links between genotype and phenotype. These 3D disease models have been used to model cancer, infectious disease, toxicity, neurological disorders, and others. In this review, we provide an overview of omics technologies, highlight current and emerging studies, discuss the associated experimental design considerations, barriers and challenges of omics technologies, and provide an outlook on the future applications of omics technologies with 3D models. Overall, this review aims to provide a valuable resource for tissue engineers seeking to leverage omics technologies for diving deeper into biological discovery. Impact statement With the emergence of three-dimensional (3D) in vitro disease models, tissue engineers are increasingly interested to investigate these systems to address biological questions related to disease mechanism, drug target discovery, therapy resistance, and more. Omics technologies are a powerful and high-throughput approach, but their application for 3D disease models is not maximally utilized. This review illustrates the achievements and potential of using omics technologies to leverage the full potential of 3D in vitro disease models. This will improve the quality of such models, advance our understanding of disease, and contribute to therapy development.

Oscillating lncRNA Platr4 regulates NLRP3 inflammasome to ameliorate nonalcoholic steatohepatitis in mice

Background: Understanding the molecular events and mechanisms underlying development and progression of nonalcoholic steatohepatitis is essential in an attempt to formulating a specific treatment. Here, we uncover Platr4 as an oscillating and NF-κB driven lncRNA that is critical to the pathological conditions in experimental steatohepatitis Methods: RNA-sequencing of liver samples was used to identify differentially expressed lncRNAs. RNA levels were analyzed by qPCR and FISH assays. Proteins were detected by immunoblotting and ELISA. Luciferase reporter, ChIP-sequencing and ChIP assays were used to investigate transcriptional gene regulation. Protein interactions were evaluated by Co-IP experiments. The protein-RNA interactions were studied using FISH, RNA pull-down and RNA immunoprecipitation analyses Results: Cyclic expression of Platr4 is generated by the core clock component Rev-erbα via two RevRE elements (i.e., -1354/-1345 and -462/-453 bp). NF-κB transcriptionally drives Platr4 through direct binding to two κB sites (i.e., -1066/-1056 and -526/-516 bp), potentially accounting for up-regulation of Platr4 in experimental steatohepatitis. Intriguingly, Platr4 serves as a circadian repressor of Nlrp3 inflammasome pathway by inhibiting NF-κB-dependent transcription of the inflammasome components Nlrp3 and Asc. Loss of Platr4 down-regulates Nlrp3 inflammasome activity in the liver, blunts its diurnal rhythm, and sensitizes mice to experimental steatohepatitis, whereas overexpression of Platr4 ameliorates the pathological conditions in an Nlrp3-dependent manner. Mechanistically, Platr4 prevents binding of the NF-κB/Rxrα complex to the κB sites via a physical interaction, thereby inhibiting the transactivation of Nlrp3 and Asc by NF-κB. Conclusions:Platr4 functions to inactivate Nlrp3 inflammasome via intercepting NF-κB signaling. This lncRNA might be an attractive target that can be modulated to ameliorate the pathological conditions of steatohepatitis.

The potential of long noncoding RNAs for precision medicine in human cancer

Precision medicine promises to better classify patients by individual clinical and biological biomarkers, which may provide an accurate assessment of disease risk, diagnosis, prognosis and treatment response. Cancer frequently displays substantial inter-tumor and intra-tumor heterogeneity and hence oncology is well suited for application of precision approaches. Recent studies have demonstrated that dysregulated lncRNAs play pivotal roles in tumor heterogeneity. In this review, attention is focused on the potential applications of lncRNAs as biomarker candidates for cancer risk evaluation, detection, surveillance and prognosis. LncRNAs are often stable in clinical samples and easily detected. The functional implications and therapeutic potential of targeting lncRNAs in human cancer are further discussed. Finally, existing deficiencies and future perspectives in translating fundamental lncRNA knowledge into clinical practice are highlighted.

MaTAR25 lncRNA regulates the Tensin1 gene to impact breast cancer progression

Misregulation of long non-coding RNA (lncRNA) genes has been linked to a wide variety of cancer types. Here we report on Mammary Tumor Associated RNA 25 (MaTAR25), a nuclear enriched and chromatin associated lncRNA that plays a role in mammary tumor cell proliferation, migration, and invasion, both in vitro and in vivo. MaTAR25 functions by interacting with purine rich element binding protein B (PURB), and associating with a major downstream target gene Tensin1 (Tns1) to regulate its expression in trans. The Tns1 protein product is a critical component of focal adhesions linking signaling between the extracellular matrix and the actin cytoskeleton. Knockout of MaTAR25 results in down-regulation of Tns1 leading to a reorganization of the actin cytoskeleton, and a reduction of focal adhesions and microvilli. We identify LINC01271 as the human ortholog of MaTAR25, and importantly, increased expression of LINC01271 is associated with poor patient prognosis and metastasis. Our findings demonstrate that LINC01271 represents a potential therapeutic target to alter breast cancer progression.

The lncRNA Toolkit: Databases and In Silico Tools for lncRNA Analysis

Long non-coding RNAs (lncRNAs) are a rapidly expanding field of research, with many new transcripts identified each year. However, only a small subset of lncRNAs has been characterized functionally thus far. To aid investigating the mechanisms of action by which new lncRNAs act, bioinformatic tools and databases are invaluable. Here, we review a selection of computational tools and databases for the in silico analysis of lncRNAs, including tissue-specific expression, protein coding potential, subcellular localization, structural conformation, and interaction partners. The assembled lncRNA toolkit is aimed primarily at experimental researchers as a useful starting point to guide wet-lab experiments, mainly containing multi-functional, user-friendly interfaces. With more and more new lncRNA analysis tools available, it will be essential to provide continuous updates and maintain the availability of key software in the future.

Functional Screening Techniques to Identify Long Non-Coding RNAs as Therapeutic Targets in Cancer

Simple Summary

Long non-coding RNAs (lncRNAs) are a recently discovered class of molecules in the cell, with potential to be utilized as therapeutic targets in cancer. A number of lncRNAs have been described to play important roles in tumor progression and drive molecular processes involved in cell proliferation, apoptosis or invasion. However, the vast majority of lncRNAs have not been studied in the context of cancer thus far. With the advent of CRISPR/Cas genome editing, high-throughput functional screening approaches to identify lncRNAs that impact cancer growth are becoming more accessible. Here, we review currently available methods to study hundreds to thousands of lncRNAs in parallel to elucidate their role in tumorigenesis and cancer progression.

Abstract

Recent technological advancements such as CRISPR/Cas-based systems enable multiplexed, high-throughput screening for new therapeutic targets in cancer. While numerous functional screens have been performed on protein-coding genes to date, long non-coding RNAs (lncRNAs) represent an emerging class of potential oncogenes and tumor suppressors, with only a handful of large-scale screens performed thus far. Here, we review in detail currently available screening approaches to identify new lncRNA drivers of tumorigenesis and tumor progression. We discuss the various approaches of genomic and transcriptional targeting using CRISPR/Cas9, as well as methods to post-transcriptionally target lncRNAs via RNA interference (RNAi), antisense oligonucleotides (ASOs) and CRISPR/Cas13. We discuss potential advantages, caveats and future applications of each method to provide an overview and guide on investigating lncRNAs as new therapeutic targets in cancer.

Optimal, Large-Scale Propagation of Mouse Mammary Tumor Organoids

Tumor organoids mimic the architecture and heterogeneity of in vivo tumors and enable studies of collective interactions between tumor cells as well as with their surrounding microenvironment. Although tumor organoids hold significant promise as cancer models, they are also more costly and labor-intensive to cultivate than traditional 2D cell culture. We sought to identify critical factors regulating organoid growth ex vivo, and to use these observations to develop a more efficient organoid expansion method. Using time-lapse imaging of mouse mammary tumor organoids in 3D culture, we observed that outgrowth potential varies non-linearly with initial organoid size. Maximal outgrowth occurred in organoids with a starting size between ~10 to 1000 cells. Based on these observations, we developed a suspension culture method that maintains organoids in the ideal size range, enabling expansion from 1 million to over 100 million cells in less than 2 weeks and less than 3 hours of hands-on time. Our method facilitates the rapid, cost-effective expansion of organoids for CRISPR based studies and other assays requiring a large amount of organoid starting material.

Identification and characterization of functional long noncoding RNAs in cancer

Long noncoding RNAs (lncRNAs) have emerged as key regulators in a variety of cellular processes that influence disease states. In particular, many lncRNAs are genetically or epigenetically deregulated in cancer. However, whether lncRNA alterations are passengers acquired during cancer progression or can act as tumorigenic drivers is a topic of ongoing investigation. In this review, we examine the current methodologies underlying the identification of cancer-associated lncRNAs and highlight important considerations for evaluating their biological significance as cancer drivers.

Prognostic value of long non-coding RNAs in triple negative breast cancer: A PRISMA-compliant meta-analysis

BACKGROUND

Triple-negative breast cancer (TNBC) is the most aggressive and lethal subtype of breast cancer. Accumulating evidence showed long non-coding RNAs (lncRNAs) are abnormally expressed in TNBC and could be valuable prognostic tools for TNBC patients. This study aims to research the prognostic value of lncRNAs in TNBC, using the meta-analysis method.

METHODS

We performed a detailed literature search on Pubmed, Scopus, and Web of Science for studies on the prognostic value of lncRNAs in TNBC. The meta-analysis method was used to determine the relationship between lncRNAs expression and survival of TNBC patients.

RESULTS

A total of 2803 TNBC patients and 24 lncRNAs from 27 different articles were included in the present study. Subgroup analysis demonstrated that overexpression of lncRNAs in a group that is upregulated in TBNC showed a significant association with poor overall survival (HR = 1.86, 95%CI = 1.45-2.27, I = 41.9%) and disease-free survival (HR = 1.85, 95%CI = 1.37-2.33, I = 0%). Conversely, overexpression of lncRNAs in a downregulation group was markedly related to good overall survival (HR = 0.60, 95%CI = 0.43-0.77, I = 28.6%). Moreover, expression of lncRNA SNHG12, MALAT1, HOTAIR, HIF1A-AS2, HULC, LINC00096, ZEB2-AS1, LUCAT1, and LINC000173 showed a marked correlation with positive lymph node metastasis (LNM), while lncRNA MIR503HG, GAS5, TCONS_l2_00002973 showed the opposite effect. High expression level of MALAT1, HIF1A-AS2, HULC, LINC00096, ADPGK-AS1, ZEB2-AS1, LUCAT1 were positively correlated with distant metastasis (DM), while lncRNA MIR503HG showed the opposite effect. In addition, the mechanisms of lncRNAs in TNBC were summarized.

CONCLUSIONS

This meta-analysis demonstrated that abnormally expressed lncRNA were significantly associated with the survival of TNBC patients and may serve as biomarkers and therapeutic targets for TNBC prognosis.

Hub Proteins Involved in RAW 264.7 Macrophages Exposed to Direct Current Electric Field

At present, studies on macrophage proteins mainly focus on biological stimuli, with less attention paid to the responses of macrophage proteins to physical stimuli, such as electric fields. Here, we exploited the electric field-sensitive hub proteins of macrophages. RAW 264.7 macrophages were treated with a direct current electric field (dcEF) (200 mV/mm) for four hours, followed by RNA-Seq analysis. Differentially expressed genes (DEGs) were obtained, followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) and protein–protein interaction (PPI) analysis. Eight qPCR-verified DEGs were selected. Subsequently, three-dimensional protein models of DEGs were modeled by Modeller and Rosetta, followed by molecular dynamics simulation for 200 ns with GROMACS. Finally, dcEFs (10, 50, and 500 mV/mm) were used to simulate the molecular dynamics of DEG proteins for 200 ns, followed by trajectory analysis. The dcEF has no obvious effect on RAW 264.7 morphology. A total of 689 DEGs were obtained, and enrichment analysis showed that the steroid biosynthesis pathway was most affected by the dcEF. Moreover, the three-dimensional protein structures of hub proteins were constructed, and trajectory analysis suggested that the dcEF caused an increase in the atomic motion of the protein in a dcEF-intensity-dependent manner. Overall, we provide new clues and a basis for investigating the hub proteins of macrophages in response to electric field stimulation.

Long non-coding RNAs in cutaneous biology and proliferative skin diseases: Advances and perspectives

Advances in transcriptome sequencing have revealed that the genome fraction largely encodes for thousands of non‐coding RNAs. Long non‐coding RNAs (lncRNAs), which are a class of non–protein‐coding RNAs longer than approximately 200 nucleotides in length, are emerging as key epigenetic regulators of gene expression recently. Intensive studies have characterized their crucial roles in cutaneous biology and diseases. In this review, we address the promotive or suppressive effects of lncRNAs on cutaneous physiological processes. Then, we focus on the pathogenic role of dysfunctional lncRNAs in a variety of proliferative skin diseases. These evidences suggest that lncRNAs have indispensable roles in the processes of skin biology. Additionally, lncRNAs might be promising biomarkers and therapeutic targets for cutaneous disorders.

LncRNA MALAT1 promotes epithelial-to-mesenchymal transition of esophageal cancer through Ezh2-Notch1 signaling pathway

To investigate effect of long noncoding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) on epithelial-to-mesenchymal transition (EMT) of esophageal cancer (EC) and role of enhancer of zeste homolog 2 (Ezh2)-Notch1 signaling pathway in the process. The expression of MALAT1 was determined in four EC cell lines by real-time PCR. TE-1 and EC109 cells were transfected with sh-MALAT1 to inhibit expression of MALAT1 or transfected with pcDNA3.1-Ezh2 to overexpress Ezh2. Invasion and migration assays were conducted to analyze cell metastasis, and expressions of Ezh2-Notch1 signaling-related proteins as well as EMT related proteins were determined using both real-time PCR and western blot. MALAT1 was significantly up-regulated in all EC cell lines compared with the normal cells. Silencing MALAT1 using shRNA could significantly inhibit cell viability (reduced almost 30% of cell viability compared with the control), invasion (reduced almost 30% of cell migration compared with the control), and migration (reduced almost 50% of cell migration compared with the control) of both TE-1 and EC109 cells (P<0.05). Meanwhile, expression of Ezh2, Notch1, Hes1, MMP-9, and Vimentin was significantly decreased and expression of E-cadherin was significantly increased when cells were transfected with sh-MALAT1 compared with the nontransfected cells (P<0.05). However, when cells were cotransfected with both sh-MALAT1 and pcDNA3.1-Ezh2, the protein expression changes induced by sh-MALAT1 were recovered. MALAT1 could affect EMT and metastasis of EC cells through Ezh2-Notch1 signaling pathway. This study can give deeper understandings of the role of MALAT1 in EC and may provide some new directions for treatment of patients with EC.

Breast tumour organoids: promising models for the genomic and functional characterisation of breast cancer

Until recently, established cancer cell lines have been used extensively in breast cancer research, due largely to the difficulties associated with the manipulation and long-term maintenance in culture of primary tumour cells from patients. The recent development of organoid cultures has provided new opportunities to model and analyse patient samples, allowing the propagation of malignant cells under conditions that resemble the three-dimensional growth of breast tumours. They have proved efficacious in preserving the heterogeneity of primary samples and are emerging as a new model to further characterise the molecular features of breast cancer. Organoids formed from patient-derived cells are now in use for the evaluation of drug sensitivity and to validate disease-causing genomic variations. Here, the advantages and limitations of organoid cultures will be discussed and compared with the parallel development of other two- and three-dimensional culture strategies and with patient-derived xenografts. In particular, we will focus on the molecular characterisation of breast cancer organoids and provide some examples of how they have been used in functional studies.

Coregulatory long non-coding RNA and protein-coding genes in serum starved cells

Serum starvation is widely used in cell biology to trigger cell cycle arrest, apoptosis, autophagy, and metabolic adaptations. Serum starvation-related molecular events have been well characterized at protein level but not at transcript level: how long non-coding RNAs contribute to the regulation of protein-coding genes is largely unknown. Here, we captured the lncRNA transcriptome in serum starved mouse embryonic fibroblasts and identified three main modes of action: cis-acting/coregulatory, trans-acting, and "miRNA-carrier". Whole-genome and individual gene level analyses support that our annotation provides an important platform for understanding lncRNA/protein-coding gene coregulatory mechanisms in serum starvation.

The regulatory roles of lncRNAs in the process of breast cancer invasion and metastasis

Breast cancer (BC) is the most common cancer and principal cause of death among females worldwide. Invasion and metastasis are major causes which influence the survival and prognosis of BC. Therefore, to understand the molecule mechanism underlying invasion and metastasis is paramount for developing strategies to improve survival and prognosis in BC patients. Recent studies have reported that long non-coding RNAs (lncRNAs) play critical roles in the regulation of BC invasion and metastasis through a variety of molecule mechanisms that endow cells with an aggressive phenotype. In this article, we focused on the function of lncRNAs on BC invasion and metastasis through participating in epithelial-to-mesenchymal transition, strengthening cancer stem cells generation, serving as competing endogenous lncRNAs, influencing multiple signaling pathways as well as regulating expressions of invasion-metastasis related factors, including cells adhesion molecules, extracellular matrix, and matrix metallo-proteinases. The published work described has provided a better understanding of the mechanisms underpinning the contribution of lncRNAs to BC invasion and metastasis, which may lay the foundation for the development of new strategies to prevent BC invasion and metastasis.

Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale

Increased efforts in cancer genomics research and bioinformatics are producing tremendous amounts of data. These data are diverse in origin, format, and content. As the amount of available sequencing data increase, technologies that make them discoverable and usable are critically needed. In response, we have developed a Semantic Web-based Data Browser, a tool allowing users to visually build and execute ontology-driven queries. This approach simplifies access to available data and improves the process of using them in analyses on the Seven Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org). The Data Browser makes large data sets easily explorable and simplifies the retrieval of specific data of interest. Although initially implemented on top of The Cancer Genome Atlas (TCGA) data set, the Data Browser's architecture allows for seamless integration of other data sets. By deploying it on the CGC, we have enabled remote researchers to access data and perform collaborative investigations.

Identification of a novel long noncoding RNA that promotes osteoblast differentiation

Long noncoding RNAs (lncRNAs) are a heterogeneous class of transcripts, longer than 200 nucleotides, 5'-capped, polyadenylated, and poorly conserved among mammalian species. Several studies have shown the contribution of lncRNAs to different cellular processes, including regulation of the chromatin structure, control of messenger RNA translation, regulation of gene transcription, regulation of embryonic pluripotency, and differentiation. Although limited numbers of functional lncRNAs have been identified so far, the immense regulatory potential of these RNAs is already evident, indicating that a functional characterization of lncRNAs is needed. In this study, mouse preosteoblastic cells were induced to differentiate into osteoblasts. At 3 sequential differentiation stages, total RNA was isolated and libraries were constructed for Illumina sequencing. The resulting sequences were aligned and transcript abundances were determined. New lncRNA candidates that displayed differential expression patterns during osteoblast differentiation were identified by combining bioinformatics and reverse transcription polymerase chain reaction analyses. Among these, lncRNA-1 that exhibited increased expression during osteogenesis and was downregulated during myogenesis. Importantly, knockdown of lncRNA-1 expression in primary mouse preosteoblasts was found to inhibit osteogenic differentiation, reflected by a reduced transcription of the Runx2/p57 and Sp7 bone master genes. Together, our results indicate that lncRNA-1 represents a new regulatory RNA that plays a relevant role during the early stages of osteogenesis.

Deciphering the roles of lncRNAs in breast development and disease

Breast cancer is the second leading cause of cancer related deaths in women. It is therefore important to understand the mechanisms underlying breast cancer development as well as raises the need for enhanced, non-invasive strategies for novel prognostic and diagnostic methods. The emergence of long non-coding RNAs (lncRNAs) as potential key players in neoplastic disease has received considerable attention over the past few years. This relatively new class of molecular regulators has been shown from ongoing research to act as critical players for key biological processes. Deregulated expression levels of lncRNAs have been observed in a number of cancers including breast cancer. Furthermore, lncRNAs have been linked to breast cancer initiation, progression, metastases and to limit sensitivity to certain targeted therapeutics. In this review we provide an update on the lncRNAs associated with breast cancer and mammary gland development and illustrate the versatility of such lncRNAs in gene control, differentiation and development both in normal physiological conditions and in diseased states. We also highlight the therapeutic and diagnostic potential of lncRNAs in cancer.

Therapeutic Targeting of Long Non-Coding RNAs in Cancer

Long non-coding RNAs (lncRNAs) represent a significant population of the human transcriptome. Many lncRNAs exhibit cell- and/or tissue/tumor-specific expression, making them excellent candidates for therapeutic applications. In this review we discuss examples of lncRNAs that demonstrate the diversity of their function in various cancer types. We also discuss recent advances in nucleic acid drug development with a focus on oligonucleotide-based therapies as a novel approach to inhibit tumor progression. The increased success rates of nucleic acid therapeutics provide an outstanding opportunity to explore lncRNAs as viable therapeutic targets to combat various aspects of cancer progression.

The Cancer Genomics Cloud: Collaborative, Reproducible, and Democratized-A New Paradigm in Large-Scale Computational Research

The Seven Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org) enables researchers to rapidly access and collaborate on massive public cancer genomic datasets, including The Cancer Genome Atlas. It provides secure on-demand access to data, analysis tools, and computing resources. Researchers from diverse backgrounds can easily visualize, query, and explore cancer genomic datasets visually or programmatically. Data of interest can be immediately analyzed in the cloud using more than 200 preinstalled, curated bioinformatics tools and workflows. Researchers can also extend the functionality of the platform by adding their own data and tools via an intuitive software development kit. By colocalizing these resources in the cloud, the CGC enables scalable, reproducible analyses. Researchers worldwide can use the CGC to investigate key questions in cancer genomics. Cancer Res; 77(21); e3-6. ©2017 AACR.

Antisense Oligonucleotides Targeting Y-Box Binding Protein-1 Inhibit Tumor Angiogenesis by Downregulating Bcl-xL-VEGFR2/-Tie Axes

Y-box binding protein-1 (YB-1), involved in cancer progression and chemoradiation resistance, is overexpressed in not only cancer cells but also tumor blood vessels. In this study, we investigated the potential value of amido-bridged nucleic acid (AmNA)-modified antisense oligonucleotides (ASOs) targeting YB-1 (YB-1 ASO^A) as an antiangiogenic cancer therapy. YB-1 ASO^A was superior to natural DNA-based ASO or locked nucleic acid (LNA)-modified YB-1 ASO in both knockdown efficiency and safety, the latter assessed by liver function. YB-1 ASO^A administered i.v. significantly inhibited YB-1 expression in CD31-positive angiogenic endothelial cells, but not in cancer cells, in the tumors. With regard to the mechanism of its antiangiogenic effects, YB-1 ASO^A downregulated both Bcl-xL/VEGFR2 and Bcl-xL/Tie signal axes, which are key regulators of angiogenesis, and induced apoptosis in vascular endothelial cells. In the xenograft tumor model that had low sensitivity to anti-VEGF antibody, YB-1 ASO^A significantly suppressed tumor growth; not only VEGFR2 but also Tie2 expression was decreased in tumor vessels. In conclusion, YB-1/Bcl-xL/VEGFR2 and YB-1/Bcl-xL/Tie signal axes play pivotal roles in tumor angiogenesis, and YB-1 ASO^A may be feasible as an antiangiogenic therapy for solid tumors.

A biosystems approach to identify the molecular signaling mechanisms of TMEM30A during tumor migration

Understanding the molecular mechanisms underlying cell migration, which plays an important role in tumor growth and progression, is critical for the development of novel tumor therapeutics. Overexpression of transmembrane protein 30A (TMEM30A) has been shown to initiate tumor cell migration, however, the molecular mechanisms through which this takes place have not yet been reported. Thus, we propose the integration of computational and experimental approaches by first predicting potential signaling networks regulated by TMEM30A using a) computational biology methods, b) our previous mass spectrometry results of the TMEM30A complex in mouse tissue, and c) a number of migration-related genes manually collected from the literature, and subsequently performing molecular biology experiments including the in vitro scratch assay and real-time quantitative polymerase chain reaction (qPCR) to validate the reliability of the predicted network. The results verify that the genes identified in the computational signaling network are indeed regulated by TMEM30A during cell migration, indicating the effectiveness of our proposed method and shedding light on the regulatory mechanisms underlying tumor migration, which facilitates the understanding of the molecular basis of tumor invasion.

Antisense Oligonucleotide-mediated Knockdown in Mammary Tumor Organoids

Primary mammary tumor organoids grown in 3D are an excellent system to study tumor biology. They resemble the organization and physiology of native epithelia more closely than cancer cell lines grown in 2D, and additionally model interactions with the ECM (Boj et al., 2015; Clevers, 2016; Shamir and Ewald, 2014). Mammary tumor organoids are therefore a promising model system to identify and characterize novel drivers of breast cancer that would be unlikely to be identified using 2D cell lines. Antisense oligonucleotides can be used to efficiently and specifically knockdown target genes in the cell (Bennett et al., 2017). They can be taken up freely by organoids without the need for a transfection agent, making them a convenient tool for routine lab studies and screens.